Specifications Compared
| Spec | A100 | QUADRO-RTX-4000 |
|---|---|---|
| TDP | 400W | 160W |
| VRAM | 40-80 GB | 8 GB |
| CUDA Cores | 6,912 | 2,304 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 288 |
| FP16 Performance | 312 TFLOPS | 7.1 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 7.1 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 416 GB/s |
Performance Analysis
The A100's FP16 performance of 312 TFLOPS dwarfs the Quadro RTX 4000's 7.1 TFLOPS, delivering approximately 44 times the half-precision throughput essential for accelerating neural network training and inference. In FP32, the A100 achieves 19.5 TFLOPS versus 7.1 TFLOPS, providing nearly three times the single-precision compute for scientific simulations and general graphics tasks. This disparity translates to faster model convergence during training, where FP16 tensor cores in the A100 handle massive datasets efficiently.
Memory specifications further widen the gap: the A100's 40-80 GB HBM2e VRAM supports large batch sizes in deep learning workflows, preventing out-of-memory errors common with the Quadro RTX 4000's 8 GB limit. Bandwidth at 2039 GB/s on the A100 enables rapid data movement for high-throughput inference, compared to 416 GB/s on the Quadro RTX 4000, which restricts it to smaller models or reduced batch sizes. Real-world impacts include the A100 training large language models in hours versus days on the Quadro RTX 4000.
Power consumption reflects their roles: the A100's 400W TDP sustains peak performance in data centers, while the Quadro RTX 4000's 160W suits power-constrained environments, though at reduced overall efficiency for compute-intensive jobs.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 769GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 5672GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 126GB RAM 1114GB Storage | Czechia | $1.00/GPU/hr $2.00/hr total (2×) | Available | ||
 Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
Quadro RTX 4000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.56/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $0.56/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.56/GPU/hr $1.12/hr total (2×) | Available | ||
Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.56/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.56/GPU/hr $1.12/hr total (2×) | Available |
When to Choose the A100
The A100 excels in large-scale machine learning training and inference requiring over 8 GB VRAM, such as processing models with billions of parameters. Its 312 TFLOPS FP16 performance and 2039 GB/s bandwidth handle massive datasets and large batch sizes effectively. Multi-GPU scaling via NVLink makes it preferable for distributed training in cloud environments, available from $0.45 per hour.
Enterprise scientific computing benefits from the A100's PCIe 4.0 and InfiniBand support, enabling high-speed clusters unattainable with the Quadro RTX 4000.
When to Choose the Quadro RTX 4000
The Quadro RTX 4000 fits budget-conscious visualization, CAD, and rendering tasks where 8 GB GDDR6 VRAM suffices for moderate datasets. Its 160W TDP consumes half the power of the A100, ideal for single-workstation setups without advanced cooling. Cloud pricing averages $0.56 per hour across limited offers, providing cost-effective access for non-AI professional workflows.
Light inference or prototyping on small models leverages the Quadro RTX 4000's 7.1 TFLOPS FP16 without overprovisioning resources needed for the A100.
Use Cases
LLM training demands over 40 GB VRAM and 312 TFLOPS FP16 performance, which the A100 provides; the Quadro RTX 4000's 8 GB VRAM cannot accommodate large models.
High-throughput inference benefits from the A100's 2039 GB/s bandwidth for large batch sizes; the Quadro RTX 4000's 416 GB/s limits scalability.
Fine-tuning large models requires the A100's 19.5 TFLOPS FP32 and ample HBM2e VRAM; 8 GB GDDR6 on the Quadro RTX 4000 restricts dataset sizes.
Stable Diffusion runs on the Quadro RTX 4000's 7.1 TFLOPS for smaller generations; the A100 accelerates batch processing with superior memory.
Complex simulations leverage the A100's NVLink interconnects and 400W TDP for sustained compute; the Quadro RTX 4000 lacks scaling options.
Frequently Asked Questions
Which GPU has more VRAM: A100 or Quadro RTX 4000?▾
The A100 provides 40-80 GB HBM2e VRAM, far exceeding the Quadro RTX 4000's 8 GB GDDR6. This enables the A100 to handle larger models in AI tasks. The difference supports bigger batch sizes on the A100.
How do FP16 performances compare between A100 and Quadro RTX 4000?▾
The A100 delivers 312 TFLOPS in FP16, compared to 7.1 TFLOPS on the Quadro RTX 4000. This makes the A100 about 44 times faster for half-precision training and inference. Tensor core advantages drive the A100's superiority.
What are the cloud pricing differences for A100 vs Quadro RTX 4000?▾
A100 rentals start from $0.45 per hour with an average of $1.92 per hour across 57 offers. The Quadro RTX 4000 starts and averages $0.56 per hour across 5 offers. Availability favors the A100 despite higher average costs.
Is the A100 or Quadro RTX 4000 more power efficient?▾
The Quadro RTX 4000 has a lower 160W TDP versus the A100's 400W. It suits power-limited workstations. However, the A100 offers better performance per watt for compute workloads.
What architectures power the A100 and Quadro RTX 4000?▾
The A100 uses the Ampere architecture from 2020, while the Quadro RTX 4000 employs Turing from 2018. Ampere introduces advanced tensor cores yielding 312 TFLOPS FP16. Turing limits the Quadro RTX 4000 to 7.1 TFLOPS.
Can the Quadro RTX 4000 handle machine learning like the A100?▾
The Quadro RTX 4000 manages light ML with 7.1 TFLOPS FP32 and 8 GB VRAM. It falls short for large-scale tasks needing the A100's 40-80 GB and 2039 GB/s bandwidth. Use it for prototyping only.
Which is cheaper to rent, the A100 or the Quadro RTX 4000?▾
Cloud rental prices for both the A100 and Quadro RTX 4000 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the A100 have compared to the Quadro RTX 4000?▾
The A100 has 40 to 80 GB of HBM2e memory. The Quadro RTX 4000 has 8 GB of GDDR6 memory.
Can I find A100 and Quadro RTX 4000 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the A100 and the Quadro RTX 4000?▾
The A100 uses the Ampere architecture (2020) while the Quadro RTX 4000 uses Turing (2018). The A100 delivers 43.9x the FP16 throughput and 4.9x the memory bandwidth of the Quadro RTX 4000.